Advances in Multifunctional Electronic Catheters for Precise and Intelligent Diagnosis and Therapy in Minimally Invasive Surgery.

The advent of catheter-based minimally invasive surgical instruments has provided an effective means of diagnosing and treating human disease. However, conventional medical catheter devices are limited in functionalities, hindering their ability to gather tissue information or perform precise treatment during surgery. Recently, electronic catheters have integrated various sensing and therapeutic technologies through micro/nanoelectronics, expanding their capabilities. As micro/nanoelectronic devices become more miniaturized, flexible, and stable, electronic surgical catheters are evolving from simple tools to multiplexed sensing and theranostics for surgical applications. The review on multifunctional electronic surgical catheters is lacking and thus is not conducive to the reader's comprehensive understanding of the development trend in this field. This review covers the advances in multifunctional electronic catheters for precise and intelligent diagnosis and therapy in minimally invasive surgery. It starts with the summary of clinical minimally invasive surgical instruments, followed by the background of current clinical catheter devices for sensing and therapeutic applications. Next, intelligent electronic catheters with integrated electronic components are reviewed in terms of electronic catheters for diagnosis, therapy, and multifunctional applications. It highlights the present status and development potential of catheter-based minimally invasive surgical devices, while also illustrating several significant challenges that remain to be overcome.

Multichannel microneedle dry electrode patches for minimally invasive transdermal recording of electrophysiological signals.

The collection of multiple-channel electrophysiological signals enables a comprehensive understanding of the spatial distribution and temporal features of electrophysiological activities. This approach can help to distinguish the traits and patterns of different ailments to enhance diagnostic accuracy. Microneedle array electrodes, which can penetrate skin without pain, can lessen the impedance between the electrodes and skin; however, current microneedle methods are limited to single channels and cannot achieve multichannel collection in small areas. Here, a multichannel (32 channels) microneedle dry electrode patch device was developed via a dimensionality reduction fabrication and integration approach and supported by a self-developed circuit system to record weak electrophysiological signals, including electroencephalography (EEG), electrocardiogram (ECG), and electromyography (EMG) signals. The microneedles reduced the electrode-skin contact impedance by penetrating the nonconducting stratum corneum in a painless way. The multichannel microneedle array (MMA) enabled painless transdermal recording of multichannel electrophysiological signals from the subcutaneous space, with high temporal and spatial resolution, reaching the level of a single microneedle in terms of signal precision. The MMA demonstrated the detection of the spatial distribution of ECG, EMG and EEG signals in live rabbit models, and the microneedle electrode (MNE) achieved better signal quality in the transcutaneous detection of EEG signals than did the conventional flat dry electrode array. This work offers a promising opportunity to develop advanced tools for neural interface technology and electrophysiological recording.

One-step triplex TaqMan quantitative reverse transcription polymerase chain reaction for the detection of feline coronavirus, feline panleukopenia virus, and feline leukemia virus.

Background and Aim: Feline coronavirus (FCoV), feline panleukopenia virus (FPV), and feline leukemia virus (FeLV) are prevalent throughout China and significantly threaten cat health. These viruses cause similar manifestations and pathological damage. Rapid and accurate diagnosis depends on detection in the laboratory. This study aimed to establish a reliable and rapid method for accurate detection of FCoV, FPV, and FeLV so that a definite diagnosis can be made and effective measures can be taken to prevent and control viral infection. Materials and Methods: We designed three pairs of specific primers and probes for the detection of FCoV 5' untranslated region, FPV viral protein 2, and FeLV pol genes. Recombinant plasmid constructs were generated for use as standard plasmid constructs. Optimal reaction conditions, including primer and probe concentrations, reaction cycles, and annealing temperatures, were obtained on the basis of optimization tests. One-step triplex real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was successfully established to simultaneously detect FCoV, FPV, and FeLV. The specificity, sensitivity, and repeatability of the assay were analyzed, and its applicability was validated by testing 1175 clinical samples. Results: One-step triplex RT-qPCR had a high degree of specificity only for the detection of FCoV, FPV, and FeLV; it had high sensitivity with limits of detection of 139.904, 143.099, and 152.079 copies/reaction for p-FCoV, p-FPV, and p-FeLV standard plasmid constructs, respectively, and it had reliable repeatability with 0.06%-0.87% intra-assay coefficients of variations. A total of 1175 clinical samples were examined for FCoV, FPV, and FeLV using triplex RT-qPCR, and the FCoV, FPV, and FeLV positivity rates were 18.47%, 19.91%, and 47.57%, respectively. The clinical sensitivity and specificity of one-step triplex RT-qPCR were 93.07% and 97.99%, respectively. Conclusion: We developed a rapid and reliable one-step triplex RT-qPCR method for the detection of FCoV, FPV, and FeLV, which could be used as a diagnostic tool for clinical monitoring and diagnosis.

New alkaloids from Stemona tuberosa and structural revision of tuberostemonols P and R.

Three Stemona alkaloids named stemotuberines A-C (1-3) with unique C17N frameworks, presumably formed by elimination of the C-11-C-15 lactone ring of the stichoneurine skeleton, were isolated from the roots of Stemona tuberosa. Their structures were elucidated by spectroscopic analysis, X-ray diffraction, and computational methods. Compounds 2 and 3 showed inhibition (IC50 values of 37.1 and 23.2 µM, respectively) against LPS-induced nitric oxide production in RAW 264.7 cells. In addition, concern was expressed about the reported plant origin (S. sessilifolia) of the recently described alkaloids tuberostemonols O-R (4-7), which should be S. tuberosa. NMR calculations indicated structural misassignment of these compounds except for 6. Isolation of tuberostemonol P (5) from our material of S. tuberosa allowed for a close examination of the spectroscopic data leading to the revised structure 5a. Tuberostemonol R (7) was found to have identical 1H and 13C NMR data to the well-known alkaloid croomine, and therefore its structure including relative stereochemistry must be revised as 7a.

Personalized Machine Learning-Coupled Nanopillar Triboelectric Pulse Sensor for Cuffless Blood Pressure Continuous Monitoring.

A wearable system that can continuously track the fluctuation of blood pressure (BP) based on pulse signals is highly desirable for the treatments of cardiovascular diseases, yet the sensitivity, reliability, and accuracy remain challenging. Since the correlations of pulse waveforms to BP are highly individualized due to the diversity of the patients' physiological characteristics, wearable sensors based on universal designs and algorithms often fail to derive BP accurately when applied on individual patients. Herein, a wearable triboelectric pulse sensor based on a biomimetic nanopillar layer was developed and coupled with Personalized Machine Learning (ML) to provide accurate and continuous monitoring of BP. Flexible conductive nanopillars as the triboelectric layer were fabricated through soft lithography replication of a cicada wing, which could effectively enhance the sensor's output performance to detect weak signal characteristics of pulse waveform for BP derivation. The sensors were coupled with a personalized Partial Least-Squares Regression (PLSR) ML to derive unknown BP based on individual pulse characteristics with reasonable accuracy, avoiding the issue of individual variability that was encountered by General PLSR ML or formula algorithms. The cuffless and intelligent design endow this ML-sensor as a highly promising platform for the care and treatments of hypertensive patients.

Nanopore Electroporation Device for DNA Transfection into Various Spreading and Nonadherent Cell Types.

Cell transfection plays a crucial role in the study of gene function and regulation of gene expression. The existing gene transfection methods, such as chemical carriers, viruses, electroporation, and microinjection, suffer from limitations, including cell type dependence, reliance on cellular endocytosis, low efficiency, safety concerns, and technical complexity. Nanopore-coupled electroporation offers a promising approach to localizing electric fields for efficient cell membrane perforation and nucleic acid transfection. However, the applicability of nanopore electroporation technology across different cell types lacks a systematic investigation. In this study, we explore the potential of nanopore electroporation for transfecting DNA plasmids into various cell types. Our nanopore electroporation device employs track-etched membranes as the core component. We find that nanopore electroporation efficiently transfects adherent cells, including well-spreading epithelial-like HeLa cells, cardiomyocyte-like HL-1 cells, and dendritic-cell-like DC2.4 cells. However, it shows a limited transfection efficiency in weakly spreading macrophages (RAW264.7) and suspension cells (Jurkat). To gain insights into these observations, we develop a COMSOL model, revealing that nanopore electroporation better localizes the electric field on adherent and well-spreading cells, promoting favorable membrane poration conditions. Our findings provide valuable references for advancing nanopore electroporation as a high-throughput, safe, and efficient gene transfection platform.

3D-assembled microneedle ion sensor-based wearable system for the transdermal monitoring of physiological ion fluctuations.

Monitoring human health is of considerable significance in biomedicine. In particular, the ion concentrations in blood are important reference indicators related to many diseases. Microneedle array-based sensors have enabled promising breakthroughs in continuous health monitoring due to their minimally invasive nature. In this study, we developed a microneedle sensing-array integrated system to continuously detect subcutaneous ions to monitor human health status in real time based on a fabrication strategy for assembling planar microneedle sheets to form 3D microneedle arrays. The limitations of preparing 3D microneedle structures with multiple electrode channels were addressed by assembling planar microneedle sheets fabricated via laser micromachining; the challenges of modifying closely spaced microneedle tips into different functionalized types of electrodes were avoided. The microneedle sensing system was sufficiently sensitive for detecting real-time changes in Ca2+, K+, and Na+ concentrations, and it exhibited good detection performance. The in vivo results showed that the ion-sensing microneedle array successfully monitored the fluctuations in Ca2+, K+, and Na+ in the interstitial fluids of rats in real time. By using an integrated circuit design, we constructed the proposed microneedle sensor into a wearable integrated monitoring system. The integrated system could potentially provide information feedback for diseases related to physiological ion changes.

Metabolomics Characterize the Differential Metabolic Markers between Bama Xiang Pig and Debao Pig to Identify Pork.

The Bama Xiang pig (BM) is a unique pig species in Guangxi Province, China. Compared to other breeds of domestic pig, such as the Debao pig (DB), it is smaller in size, better in meat quality, resistant to rough feeding and strong in stress resistance. These unique advantages of Bama Xiang pigs make them of great edible value and scientific research value. However, the differences in muscle metabolites between Bama Xiang pigs (BM) and Debao pigs (DB) are largely unexplored. Here, we identified 214 differential metabolites between these two pig breeds by LC-MS. Forty-one such metabolites are enriched into metabolic pathways, and these metabolites correspond to 11 metabolic pathways with significant differences. In Bama pigs, the abundance of various metabolites such as creatine, citric acid, L-valine and hypoxanthine is significantly higher than in Debao pigs, while the abundance of other metabolites, such as carnosine, is significantly lower. Among these, we propose six differential metabolites: L-proline, citric acid, ribose 1-phosphate, L-valine, creatine, and L-arginine, as well as four potential differential metabolites (without the KEGG pathway), alanyl-histidine, inosine 2'-phosphate, oleoylcarnitine, and histidinyl hydroxyproline, as features for evaluating the meat quality of Bama pigs and for differentiating pork from Bama pigs and Debao pigs. This study provides a proof-of-concept example of distinguishing pork from different pig breeds at the metabolite level and sheds light on elucidating the biological processes underlying meat quality differences. Our pork metabolites data are also of great value to the genomics breeding community in meat quality improvement.

Study on Multi-Model Soft Sensor Modeling Method and Its Model Optimization for the Fermentation Process of Pichia pastoris.

The problems that the key biomass variables in Pichia pastoris fermentation process are difficult measure in real time; this paper mainly proposes a multi-model soft sensor modeling method based on the piecewise affine (PWA) modeling method, which is optimized by particle swarm optimization (PSO) with an improved compression factor (ICF). Firstly, the false nearest neighbor method was used to determine the order of the PWA model. Secondly, the ICF-PSO algorithm was proposed to cooperatively optimize the number of PWA models and the parameters of each local model. Finally, a least squares support vector machine was adopted to determine the scope of action of each local model. Simulation results show that the proposed ICF-PSO-PWA multi-model soft sensor modeling method accurately approximated the nonlinear features of Pichia pastoris fermentation, and the model prediction accuracy is improved by 4.4884% compared with the weighted least squares vector regression model optimized by PSO.

Optically Programmable Plateau-Rayleigh Instability for High-Resolution and Scalable Morphology Manipulation of Silver Nanowires for Flexible Optoelectronics.

The ability to engineer microscale and nanoscale morphology upon metal nanowires (NWs) has been essential to achieve new electronic and photonic functions. Here, this study reports an optically programmable Plateau-Rayleigh instability (PRI) to demonstrate a facile, scalable, and high-resolution morphology engineering of silver NWs (AgNWs) at temperatures <150 °C within 10 min. This has been accomplished by conjugating a photosensitive diphenyliodonium nitrate with AgNWs to modulate surface-atom diffusion. The conjugation is UV-decomposable and able to form a cladding of molten salt-like compounds, so that the PRI of the AgNWs can be optically programmed and triggered at a much lower temperature than the melting point of AgNWs. This PRI self-assembly technique can yield both various novel nanostructures from single NW and large-area microelectrodes from the NW network on various substrates, such as a nanoscale dot-dash chain and the microelectrode down to 5 µm in line width that is the highest resolution ever fabricated for the AgNW-based electrode. Finally, the patterned AgNWs as flexible transparent electrodes were demonstrated for a wearable CdS NW photodetector. This study provides a new paradigm for engineering metal micro-/nanostructures, which holds great potential in fabrication of various sophisticated devices.